Structure, stability and elasticity of DNA nanotubes

DNA nanotubes are tubular structures composed of DNA crossover molecules. We present a bottom up approach for the construction and characterization of these structures. Various possible topologies of nanotubes are constructed such as 6-helix, 8-helix and tri-tubes with different sequences and lengths. We have used fully atomistic molecular dynamics simulations to study the structure, stability and elasticity of these structures. Several nanosecond long MD simulations give the microscopic details about DNA nanotubes. Based on the structural analysis of simulation data, we show that 6-helix nanotubes are stable and maintain their tubular structure; while 8-helix nanotubes are flattened to stabilize themselves. We also comment on the sequence dependence and the effect of overhangs. These structures are approximately four times more rigid having a stretch modulus of similar to 4000 pN compared to the stretch modulus of 1000 pN of a DNA double helix molecule of the same length and sequence. The stretch moduli of these nanotubes are also three times larger than those of PX/JX crossover DNA molecules which have stretch moduli in the range of 1500-2000 pN. The calculated persistence length is in the range of a few microns which is close to the reported experimental results on certain classes of DNA nanotubes.

Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mgha(-1)) at spatial scales ranging from 5 to 250m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial ``dilution'' bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

Phytoplankton size structure in the southern Bay of Bengal modified by the Summer Monsoon Current and associated eddies: Implications on the vertical biogenic flux

The present study combines field and satellite observations to investigate how hydrographical transformations influence phytoplankton size structure in the southern Bay of Bengal during the peak Southwest Monsoon/Summer Monsoon (July-August). The intrusion of the Summer Monsoon Current (SMC) into the Bay of Bengal and associated changes in sea surface chemistry, traceable eastward up to 90 degrees E along 8 degrees N, seems to influence biology of the region significantly. Both in situ and satellite (MODIS) data revealed low surface chlorophyll except in the area influenced by the SMC During the study period, two well-developed cydonic eddies (north) and an anti-cyclonic eddy (south), closely linked to the main eastward flow of the SMC, were sampled. Considering the capping effect of the low-saline surface water that is characteristic of the Bay of Bengal, the impact of the cyclonic eddy, estimated in terms of enhanced nutrients and chlorophyll, was mostly restricted to the subsurface waters (below 20 m depth). Conversely, the anti-cyclonic eddy aided by the SMC was characterized by considerably higher nutrient concentration and chlorophyll in the upper water column (upper 60 m), which was contrary to the general characteristic of such eddies. Albeit smaller phytoplankton predominated the southern Bay of Bengal (60-95% of the total chlorophyll), the contribution of large phytoplankton was double in the regions influenced by the SMC and associated eddies. Multivariate analysis revealed the extent to which SMC-associated eddies spatially influence phytoplankton community structure. The study presents the first direct quantification of the size structure of phytoplankton from the southern Bay of Bengal and demonstrates that the SMC-associated hydrographical ramifications significantly increase the phytoplankton biomass contributed by larger phytoplankton and thereby influence the vertical opal and organic carbon flux in the region. (C) 2014 Elsevier B.V. All rights reserved.

Crystal Structure and Prediction

The notion of structure is central to the subject of chemistry. This review traces the development of the idea of crystal structure since the time when a crystal structure could be determined from a three-dimensional diffraction pattern and assesses the feasibility of computationally predicting an unknown crystal structure of a given molecule. Crystal structure prediction is of considerable fundamental and applied importance, and its successful execution is by no means a solved problem. The ease of crystal structure determination today has resulted in the availability of large numbers of crystal structures of higher-energy polymorphs and pseudopolymorphs. These structural libraries lead to the concept of a crystal structure landscape. A crystal structure of a compound may accordingly be taken as a data point in such a landscape.

Online_DPI: a web server to calculate the diffraction precision index for a protein structure

An online computing server, Online_DPI (where DPI denotes the diffraction precision index), has been created to calculate the `Cruickshank DPI' value for a given three-dimensional protein or macromolecular structure. It also estimates the atomic coordinate error for all the atoms available in the structure. It is an easy-to-use web server that enables users to visualize the computed values dynamically on the client machine. Users can provide the Protein Data Bank (PDB) identification code or upload the three-dimensional atomic coordinates from the client machine. The computed DPI value for the structure and the atomic coordinate errors for all the atoms are included in the revised PDB file. Further, users can graphically view the atomic coordinate error along with `temperature factors' (i.e. atomic displacement parameters). In addition, the computing engine is interfaced with an up-to-date local copy of the Protein Data Bank. New entries are updated every week, and thus users can access all the structures available in the Protein Data Bank. The computing engine is freely accessible online at http://cluster.physics.iisc.ernet.in/dpi/.

The crystal structure of a lectin from Butea monosperma: Insight into its glycosylation and binding of ligands

Crystal structure of a lectin purified from Butea monosperma seeds was determined by Molecular Replacement method. Its primary structure was determined by Tandem Mass Spectroscopy and electron density maps from X-ray diffraction data. Its quaternary structure was tetrameric, formed of two monomers, alpha and beta, beta appearing as truncated alpha. The occurrence of two tetramers in the asymmetric unit of the crystal might be a consequence of asymmetric contacts due to difference in glycosylation and variable loops structures, to form an `octamer-structure'. The crystal structure showed binding pockets for gamma Abu, having a proposed role in plant defense, at the interface of canonical dimer-partners. Hemagglutination studies, enzyme kinetics, isothermal titration calorimetry and molecular dynamics showed that the lectin is specific to N-acetyl D-galactosamine, galactose and lactose in decreasing order, and alpha-amylase inhibitor. (C) 2014 Elsevier B.V. All rights reserved.

Suspensions of polymer-grafted nanoparticles with added polymers-Structure and effective pair-interactions

We present the results of combined experimental and theoretical (molecular dynamics simulations and integral equation theory) studies of the structure and effective interactions of suspensions of polymer grafted nanoparticles (PGNPs) in the presence of linear polymers. Due to the absence of systematic experimental and theoretical studies of PGNPs, it is widely believed that the structure and effective interactions in such binary mixtures would be very similar to those of an analogous soft colloidal material-star polymers. In our study, polystyrene-grafted gold nanoparticles with functionality f = 70 were mixed with linear polystyrene (PS) of two different molecular weights for obtaining two PGNP: PS size ratios, xi = 0.14 and 2.76 (where, xi = M-g/M-m, M-g and M-m being the molecular weights of grafting and matrix polymers, respectively). The experimental structure factor of PGNPs could be modeled with an effective potential (Model-X), which has been found to be widely applicable for star polymers. Similarly, the structure factor of the blends with xi = 0.14 could be modeled reasonably well, while the structure of blends with xi = 2.76 could not be captured, especially for high density of added polymers. A model (Model-Y) for effective interactions between PGNPs in a melt of matrix polymers also failed to provide good agreement with the experimental data for samples with xi = 2.76 and high density of added polymers. We tentatively attribute this anomaly in modeling the structure factor of blends with xi = 2.76 to the questionable assumption of Model-X in describing the added polymers as star polymers with functionality 2, which gets manifested in both polymer-polymer and polymer-PGNP interactions especially at higher fractions of added polymers. The failure of Model-Y may be due to the neglect of possible many-body interactions among PGNPs mediated by matrix polymers when the fraction of added polymers is high. These observations point to the need for a new framework to understand not only the structural behavior of PGNPs but also possibly their dynamics and thermo-mechanical properties as well. (C) 2015 AIP Publishing LLC.

Evaluation of Precipitation Retrievals From Orbital Data Products of TRMM Over a Subtropical Basin in India

The spatial error structure of daily precipitation derived from the latest version 7 (v7) tropical rainfall measuring mission (TRMM) level 2 data products are studied through comparison with the Asian precipitation highly resolved observational data integration toward evaluation of the water resources (APHRODITE) data over a subtropical region of the Indian subcontinent for the seasonal rainfall over 6 years from June 2002 to September 2007. The data products examined include v7 data from the TRMM radiometer Microwave Imager (TMI) and radar precipitation radar (PR), namely, 2A12, 2A25, and 2B31 (combined data from PR and TMI). The spatial distribution of uncertainty from these data products were quantified based on performance metrics derived from the contingency table. For the seasonal daily precipitation over a subtropical basin in India, the data product of 2A12 showed greater skill in detecting and quantifying the volume of rainfall when compared with the 2A25 and 2B31 data products. Error characterization using various error models revealed that random errors from multiplicative error models were homoscedastic and that they better represented rainfall estimates from 2A12 algorithm. Error decomposition techniques performed to disentangle systematic and random errors verify that the multiplicative error model representing rainfall from 2A12 algorithm successfully estimated a greater percentage of systematic error than 2A25 or 2B31 algorithms. Results verify that although the radiometer derived 2A12 rainfall data is known to suffer from many sources of uncertainties, spatial analysis over the case study region of India testifies that the 2A12 rainfall estimates are in a very good agreement with the reference estimates for the data period considered.

Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach

The impulse response of wireless channels between the N-t transmit and N-r receive antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), i.e., NtNt the channels have a small number of significant paths relative to the channel delay spread and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wireless channels are also group approximately cluster-sparse (gac-sparse), i.e., every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this paper, we cast the problem of estimating the ga-sparse and gac-sparse block-fading and time-varying channels in the sparse Bayesian learning (SBL) framework and propose a bouquet of novel algorithms for pilot-based channel estimation, and joint channel estimation and data detection, in MIMO-OFDM systems. The proposed algorithms are capable of estimating the sparse wireless channels even when the measurement matrix is only partially known. Further, we employ a first-order autoregressive modeling of the temporal variation of the ga-sparse and gac-sparse channels and propose a recursive Kalman filtering and smoothing (KFS) technique for joint channel estimation, tracking, and data detection. We also propose novel, parallel-implementation based, low-complexity techniques for estimating gac-sparse channels. Monte Carlo simulations illustrate the benefit of exploiting the gac-sparse structure in the wireless channel in terms of the mean square error (MSE) and coded bit error rate (BER) performance.

Divide and Conquer: Efficient Large-Scale Structure from Motion Using Graph Partitioning

Despite significant advances in recent years, structure-from-motion (SfM) pipelines suffer from two important drawbacks. Apart from requiring significant computational power to solve the large-scale computations involved, such pipelines sometimes fail to correctly reconstruct when the accumulated error in incremental reconstruction is large or when the number of 3D to 2D correspondences are insufficient. In this paper we present a novel approach to mitigate the above-mentioned drawbacks. Using an image match graph based on matching features we partition the image data set into smaller sets or components which are reconstructed independently. Following such reconstructions we utilise the available epipolar relationships that connect images across components to correctly align the individual reconstructions in a global frame of reference. This results in both a significant speed up of at least one order of magnitude and also mitigates the problems of reconstruction failures with a marginal loss in accuracy. The effectiveness of our approach is demonstrated on some large-scale real world data sets.

Molecular structure of the discotic liquid crystalline phase of hexa-peri-hexabenzocoronene/oligothiophene hybrid and their charge transport properties

Using atomistic molecular dynamics simulation, we study the discotic columnar liquid crystalline (LC) phases formed by a new organic compound having hexa-peri-Hexabenzocoronene (HBC) core with six pendant oligothiophene units recently synthesized by Nan Hu et al. Adv. Mater. 26, 2066 (2014)]. This HBC core based LC phase was shown to have electric field responsive behavior and has important applications in organic electronics. Our simulation results confirm the hexagonal arrangement of columnar LC phase with a lattice spacing consistent with that obtained from small angle X-ray diffraction data. We have also calculated various positional and orientational correlation functions to characterize the ordering of the molecules in the columnar arrangement. The molecules in a column are arranged with an average twist of 25 degrees having an average inter-molecular separation of similar to 5 angstrom. Interestingly, we find an overall tilt angle of 43 degrees between the columnar axis and HBC core. We also simulate the charge transport through this columnar phase and report the numerical value of charge carrier mobility for this liquid crystal phase. The charge carrier mobility is strongly influenced by the twist angle and average spacing of the molecules in the column. (C) 2015 AIP Publishing LLC.

Local structure of boundary layer transition in experiments with a single streamwise vortex

Transition induced by an isolated streamwise vortex embedded in a flat plate boundary layer was studied experimentally. The vortex was created by a gentle hill with a Gaussian profile that spanned on half of the width of a flat plate mounted in a low turbulence wind tunnel. PIV and hot-wire anemometry data were taken. Transition occurs as a non-inclined shear layer breaks up into a sequence of vortices, close to the boundary layer edge. The passing frequency of these vortices scales with square of the freestream velocity, similar to that in single-roughness induced transition. Quadrant analysis of streamwise and wall-normal velocity fluctuations show large ejection events in the outer layer. (C) 2015 Elsevier Inc. All rights reserved.

Event-triggered Sampling and Reconstruction of Sparse Real-valued Trigonometric Polynomials

We propose data acquisition from continuous-time signals belonging to the class of real-valued trigonometric polynomials using an event-triggered sampling paradigm. The sampling schemes proposed are: level crossing (LC), close to extrema LC, and extrema sampling. Analysis of robustness of these schemes to jitter, and bandpass additive gaussian noise is presented. In general these sampling schemes will result in non-uniformly spaced sample instants. We address the issue of signal reconstruction from the acquired data-set by imposing structure of sparsity on the signal model to circumvent the problem of gap and density constraints. The recovery performance is contrasted amongst the various schemes and with random sampling scheme. In the proposed approach, both sampling and reconstruction are non-linear operations, and in contrast to random sampling methodologies proposed in compressive sensing these techniques may be implemented in practice with low-power circuitry.

Protein Structure and Function: Looking through the Network of Side-Chain Interactions

Network theory has become an excellent method of choice through which biological data are smoothly integrated to gain insights into complex biological problems. Understanding protein structure, folding, and function has been an important problem, which is being extensively investigated by the network approach. Since the sequence uniquely determines the structure, this review focuses on the networks of non-covalently connected amino acid side chains in proteins. Questions in structural biology are addressed within the framework of such a formalism. While general applications are mentioned in this review, challenging problems which have demanded the attention of scientific community for a long time, such as allostery and protein folding, are considered in greater detail. Our aim has been to explore these important problems through the eyes of networks. Various methods of constructing protein structure networks (PSN) are consolidated. They include the methods based on geometry, edges weighted by different schemes, and also bipartite network of protein-nucleic acid complexes. A number of network metrics that elegantly capture the general features as well as specific features related to phenomena, such as allostery and protein model validation, are described. Additionally, an integration of network theory with ensembles of equilibrium structures of a single protein or that of a large number of structures from the data bank has been presented to perceive complex phenomena from network perspective. Finally, we discuss briefly the capabilities, limitations, and the scope for further explorations of protein structure networks.

Neutron powder diffraction study of Ba3ZnRu2-xIrxO9 (x=0, 1, 2) with 6H-type perovskite structure

The triple perovskites Ba3ZnRu2-xIrxO9 with x = 0, 1, and 2 are insulating compounds in which Ru(Ir) cations form a dimer state. Polycrystalline samples of these materials were studied using neutron powder diffraction (NPD) at 10 and 295 K. No structural transition nor evidence of long range magnetic order was observed within the investigated temperature range. The results from structural refinements of the NPD data and its polyhedral analysis are presented, and discussed as a function of Ru/Ir content. (C) 2015 Elsevier Masson SAS. All rights reserved.